Early Strokes Are Associated with More Global Cognitive Deficits in Adults with Sickle Cell Disease
Bibliographic record
Abstract
This study sought to link neurocognitive profiles in sickle cell disease (SCD) patients with clinical characteristics. We conducted a prospective cohort study of adults with SCD who underwent comprehensive neuropsychological assessment at the UMGGR clinic at Henri Mondor Hospital, Créteil (France). A cluster analysis was performed based on neuropsychological testing scores. The association between clusters and clinical profiles was assessed. Between 2017 and 2021, 79 patients with a mean age of 36 [range 19–65] years were included. On principal component analysis, a 5-factor model presented the best fit (Bartlett’s sphericity test [χ2 (171) = 1345; p < 0.001]), explaining 72% of the variance. The factors represent distinct cognitive domains and anatomical regions. On hierarchical classification, three clusters emerged. Cluster 1 (n = 24) presented deficits in all five factors compared to Cluster 3 (n = 33). Cluster 2 (n = 22) had deficits in all factors, but to a lesser extent than Cluster 1. MoCA scores mirrored the severity of these cognitive deficits. Age, genotype and stroke prevalence did not differ significantly between clusters. However, the time of first stroke occurrence differed significantly between Cluster 1 and 2–3: 78% of strokes occurred during childhood, whereas 80% and 83% occurred during adulthood in Clusters 2 and 3, respectively. Educational attainment was also reduced in Cluster 1. SCD patients with childhood stroke seem to be at increased risk of a global cognitive deficit profile. In addition to existing methods of primary and secondary stroke prevention, early neurorehabilitation should be prioritized in order to reduce the long-term cognitive morbidity of SCD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".